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Control of processes with noise and time delays
Author(s) -
Walgama Kirthi S.,
Fisher D. Grant,
Shah Sirish L.
Publication year - 1989
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690350205
Subject(s) - control theory (sociology) , kalman filter , transfer function , smith predictor , noise (video) , compensation (psychology) , state space , variance (accounting) , state space representation , discrete time and continuous time , mathematics , engineering , computer science , pid controller , control engineering , statistics , algorithm , control (management) , temperature control , psychology , artificial intelligence , psychoanalysis , electrical engineering , image (mathematics) , accounting , business
A stable Kalman filter predictor (KFP) is developed which generates minimum variance estimates of the future outputs { y ( t + i | t ), i = 1, … d } of stochastic, single‐input/single‐output processes with time delay, d . The predicted outputs are used for time delay compensation and in the design of a predictive feedback controller. An innovation model analysis is used to convert the state space formulation to transfer function form and to show the relationship between the KFP, the Smith predictor, and the internal model controller. A modified KFP includes a disturbance model, and eliminates offset due to deterministic disturbances (e.g., steps) and modeling errors. Simulation results show that the modified KFP also predicts the disturbances and gives significantly better performance than the Smith predictor, particularly in the presence of process and measurement noise.